4 papers
Bayesian fusion forests for heterogeneous treatment effects on survival from randomised and real-world data
Tijn Jacobs, Stéphanie L. van der Pas, Wessel N. van Wieringen
We develop the Bayesian fusion forest, a nonparametric framework to estimate heterogeneous treatment effects on survival outcomes by combining a randomised controlled trial and rea…
Horseshoe Forests for High-Dimensional Causal Survival Analysis
Tijn Jacobs, Wessel N. van Wieringen, Stéphanie L. van der Pas
We develop a Bayesian tree ensemble model to estimate heterogeneous treatment effects in censored survival data with high-dimensional covariates. Instead of imposing sparsity throu…
A Flexible Model for Record Linkage
Kayané Robach, Stéphanie L van der Pas, Mark A van de Wiel +1
Combining data from various sources empowers researchers to explore innovative questions, for example those raised by conducting healthcare monitoring studies. However, the lack of…
Bayesian regression discontinuity design with unknown cutoff
Julia Kowalska, Mark van de Wiel, Stéphanie van der Pas
The regression discontinuity design (RDD) is a quasi-experimental approach used to estimate the causal effects of an intervention assigned based on a cutoff criterion. RDD exploits…